Obesity and Inflammation: associated...

Faculdade de Medicina da Universidade do Porto

Serviço de Higiene e Epidemiologia

Obesity and Inflammation: associated polymorphisms

Mestrado em Medicina e Oncologia Molecular

Joana Bárbara de Bessa Barroso

Porto, 2008

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BEST REGARDS

Ao Professor Henrique Barros, obrigada pela oportunidade, pelos sábios conselhos e

pela orientação da tese.

A todos os colegas do Serviço de Higiene e Epidemiologia, obrigada por me receberem,

pelas opiniões e pelo contributo que deram a este trabalho.

À Ana B., obrigada pelas palavras e por todo o apoio e amizade com que sei que posso

contar.

À Sandra, obrigada pela amizade de uma vida, por toda a compreensão e por todos os

momentos que recordo com saudade.

À Fernanda, obrigada pela amizade e carinho.

Ao meu irmão, obrigada por todos os bons momentos, pela amizade e por estar presente

quando mais preciso.

Aos meus avós obrigada pelo amor incondicional e por me mostrarem todos os dias que

existem pessoas genuinamente bondosas.

Ao Artur, sem o qual a minha vida não seria a mesma, obrigada por todo o amor,

companheirismo e por todos os momentos felizes que passamos juntos.

Aos meus pais, pelas pessoas maravilhosas que são e a quem eu devo tudo o que sou,

obrigada pelo carinho, pelo apoio constante, por todo o amor e confiança que sempre

depositaram em mim.

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TABLE OF CONTENTS

ABBREVIATIONS LIST ....................................................................................................................................... 7

ABSTRACT ......................................................................................................................................................... 9

INTRODUCTION ............................................................................................................................................... 13

INFLAMMATION ........................................................................................................................................... 13 Interleukin 1........................................................................................................................................... 16 Tumor necrosis factor ............................................................................................................................ 17 Interleukin 6........................................................................................................................................... 18 C-reactive protein .................................................................................................................................. 19 Fibrinogen ............................................................................................................................................. 19 Leucocytes.............................................................................................................................................. 20 Uric Acid................................................................................................................................................ 21

OBESITY ...................................................................................................................................................... 22 OBESITY AND INFLAMMATION .................................................................................................................... 24

AIMS ................................................................................................................................................................ 27

PARTICIPANTS AND METHODS ....................................................................................................................... 29

Participants............................................................................................................................................ 29 Anthropometric measurements .............................................................................................................. 29 Measurement of CRP plasma levels....................................................................................................... 30 Genotyping............................................................................................................................................. 30 Statistical Methods................................................................................................................................. 32

CHAPTER I

IL-6 -174G/C POLYMORPHISM INTERACTS WITH ABDOMINAL ADIPOSITY TO INCREASE C-REACTIVE PROTEIN .......................................................................................................................................................... 33

RESULTS...................................................................................................................................................... 35 DISCUSSION................................................................................................................................................. 39

CHAPTER II

IL6, IL1�ETA AND TNF�LFA GENOTYPE AND FAT DISTRIBUTION: EFFECT ON INFLAMMATORY MARKERS......................................................................................................................................................................... 43

RESULTS...................................................................................................................................................... 45 DISCUSSION................................................................................................................................................. 58

Interleukin 6.......................................................................................................................................... 58 Interleukin 1� ......................................................................................................................................... 59 Tumor necrosis factor- �........................................................................................................................ 61

CONCLUSION................................................................................................................................................... 65

BIBLIOGRAPHY ............................................................................................................................................... 67

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ABBREVIATIONS LIST

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ABBREVIATIONS LIST

BMI – Body Mass Index

CRP – C-reactive protein

Fc - Fragment crystallizable

GPIIb/IIIa – Glycoprotein IIb/IIIa

GTPases - Guanine triphosphatases

IKK - I Kappa B Kinase

IL1� – Interleukin 1 beta

IL-6 – Interleukin 6

ICAM-1 - Intercellular cell adhesion molecule-1

MCP-1 - Chemotactic factor monocyte chemoattractant protein-1

(NF)-�� - Nuclear factor

TNF� – Tumor Necrosis Factor alpha

VCAM-1 - Vascular cell adhesion molecule-1

WC – Waist Circumference

WHO – World Health Organization

WHR – Waist-hip ratio

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ABSTRACT

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ABSTRACT

Objective: Obesity has been characterized by a state of chronic low-grade inflammation,

given that increased levels of the inflammatory markers have been related with adiposity.

The assumption is that adipokines, cytokines, and other factors produced and released by

fat are responsible for the chronic inflammatory state of obesity. Once that IL-6, IL-1 and

TNF are increased in adipocytes in the obese state and are early-acting inducers of

inflammatory cascades, genetically determined subsets of the population may have

altered acute phase responses to certain stimuli. Therefore, we studied the influence of fat

distribution in the inflammatory outcome phenotype of specific polymorphisms affecting

genes enconding pro-inflammatory cytokines.

Design: Cross-sectional study.

Subjects: 411 non-institutionalized inhabitants of Porto, Portugal.

Measurements: Participants answered a structured questionnaire and were genotyped for

the following polymorphisms: IL-6 -174 G/C, IL1� -511C/T, TNF� -308G/A. Analytical and

anthropometrics measurements were obtained after 12 h fasting. CRP, fibrinogen,

leukocytes and uric acid levels were measured.

Results: Genotyping of the IL-6 -174 G/C polymorphism was performed in 322 people.

There were 144 (44.7%) participants with GG genotype, 132 (41.0%) GC heterozygotes,

and 46 (14.3%) CC homozygotes. It was found a significant association between waist

circumference and C carriers – GC (�=0.039, p<0.001) and CC (�=0.037, p=0.006), within

C-reactive protein. No interaction was found between waist circumference and C carriers,

in relation to leukocytes, but this association became statistically significant after

adjustment for gender, age and smoking habits when comparing GG homozigotes with

heterozigotes GC (�=0.022, p=0.018) and with homozigotes CC (�=0.045, p=0.020).

There is a significant association between waist circumference and C carriers in relation to

uric acid levels – GC (�=0.392, p<0.001) and CC (�=0.485, p=0.007). In relation to

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fibrinogen, it was found a significant association between waist circumference and

homozigotes GG (�=-0.002, p=0.015) and GC genotype (�=0.016, p=0.006).

Genotyping of the IL1� -511 C/T polymorphism was performed in 254 subjects. There

were 110(43.3%) participants with CC genotype, 106(41.7%) heterozygotes CT, and

38(15.0%) homozygotes TT. It was found no interaction between waist circumference and

homozigotes TT, in relation to CRP concentrations. The interaction of homozigotes CC

(�=0.027, p<0.001) and heterozigotes CT (�= -0.027, p<0.001) with WC showed an effect

on CRP concentrations, even after adjustment for gender, age and smoking habits. In

relation to leukocytes, there is no interaction between waist circumference and C carriers,

but once adjusted for gender, age and smoking habits, the interaction between waist

circumference and CC homozigotes (�=0.028, p=0.009) and heterozigotes CT (�= -0.026,

p=0.018) affected leukocyte levels. No interaction was seen between waist circumference

and homozigotes TT, in relation to uric acid concentrations. The interaction of

homozigotes CC (�=0.586, p<0.001) and heterozigotes CT (�= -0.543, p<0.001) with WC

showed an effect on uric acid levels, even after adjustment for gender, age and smoking

habits. The interaction of homozigotes CC (�=0.016, p=0.038) and heterozigotes CT (�=-

0.018, p=0.021) with WC showed an effect on fibrinogen concentrations, and no

interaction was found between waist circumference and homozigotes TT.

Genotyping of the TNF-� -308 G/A polymorphism was performed in 308 subjects. There

were 228(74.0%) participants with GG genotype, 76(24.7%) heterozygotes GA, and

4(1.3%) homozygotes AA. It was found no interaction between waist circumference and

homozigotes GG and AA, in relation to CRP concentrations. The interaction of

heterozigotes GA with WC showed an effect on CRP concentrations (�= 0.038, p<0.001),

even after adjustment for gender, age and smoking habits. There is also no interaction

between waist circumference and GG, GA and AA genotypes, in relation to leukocytes

concentrations. The interaction of homozigotes GG and GA with WC showed an effect on

uric acid concentrations (�=0.056, p<0.001 and �=0.410, p=0.003, respectively), even

after adjustment for gender, age and smoking habits. It was found no interaction between

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waist circumference and genotypes GG, GA and AA, in relation to fibrinogen

concentrations. After adjustment for gender, age and smoking habits, the interaction of

homozigotes GG (�=-0.002, p=0.034) and heterozigotes GA (�= -0.017, p=0.001) with

WC showed an effect on fibrinogen concentrations.

Conclusions: For the analysed polymorphisms, there is an interaction with waist

circumference in relation to at least one inflammatory marker level.

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INTRODUCTION

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INTRODUCTION

An important recent development in our understanding of obesity is the emergence of the

concept of a state of chronic low-grade inflammation 1, as indicated by increased levels of

inflammatory markers as C-reactive protein. The current working hypothesis is that

adipokines, cytokines, and other factors produced and released by fat induce a chronic

inflammatory state. Since IL-6, IL-1 and TNF are early-acting inducers of inflammatory

cascades, genetically determined subsets of the population may have altered acute phase

responses to certain stimuli.

INFLAMMATION

The word inflammation comes from the latin “inflammare” (to set on fire). The cardinal

signs of acute inflammation were described centuries ago as redness, heat, swelling and

pain 2. Thus, in its origin, inflammation was defined by a combination of clinical signs and

symptoms, not by specific pathophysiology. This definition according to clinical signs and

symptoms had limitations, as in most cases the cellular processes and signals that

underlie the cardinal signs occur at a subclinical level and do not give rise to heat,

redness, swelling, or pain. In the 19th century new definitions arose for inflammation as a

non-specific complex stereotypical cellular response that follows trauma 2. Advances in

molecular biology placed additional complexity on this model, disclosing that tissue may

be influenced by proinflammatory signalling molecules, even in the absence of

inflammatory cell invasion and that aspects of both inflammation and repair can be

triggered and modulated by primary events occurring outside the vasculature, such as

vibration, hypoxia, and mechanical loading 2.

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Inflammation is categorized as acute or chronic. Basically, acute inflammation that has

lasted longer than a few weeks is considered chronic. At the cellular level there is a

difference in the nature of the tissue lesions, secreted effector molecules and cell types. In

acute inflammation there is an abundance of phagocytic cells (principally neutrophils and

macrophages) whereas in chronic inflammation lymphocytes and monocytes

predominate. It is clear that each type of inflammation is not a simple linear cascade, but

rather a complex, highly orchestrated and fine-tuned process, involving interactions

between many different types of cells, soluble mediators and tissue matrix 3. Inflammation

causes the immediate and sequential release of signalling factors including chemokines,

cytokines, eicosanoids, that bring leucocytes (polymorphonuclears, eosinophils) from the

microvasculature to the site of inflammation to neutralize the injurious agent 4. After

leucocyte trafficking, peripheral blood monocytes accumulate at the inflammatory site and

differentiate locally in to larger more granular phagocytosing macrophages 4. Once the

inflammatory cells have neutralized the injurious agent they must be disposed of in a

controlled and effective manner 4. Apoptotic polymorphonuclear leucocytes or eosinophils

are phagocytosed by macrophages, which in turn are cleared from the site of inflammation

either by dying locally or by programmed cell death or by clearing to the draining

lymphatics 4 (figure 1-A). Given a favourable genetic predisposition, failure of acute

inflammation to resolve adequately could result in a predisposition to chronic

inflammation, collateral tissue injury or auto-immunity typified by the accumulation of

inflammatory leucocytes fibrosis and auto-antibodies to endogenous cellular and tissue

antigens 4 (figure 1-B).

Inflammation is regulated by cytokines, chemokines, and growth factors, many of which

may be active in the chronic inflammation 5. Inflammation triggers the production of

primary proinflammatory cytokines such as IL-1� and TNF�. IL-1 and TNF are primarily

produced by monocytes and macrophages but can also be generated by a variety of

resident cells in tissues 6. These cytokines stimulate the production of chemoattractant

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cytokines (chemokines), which may play a major role in atherogenesis, and stimulate the

production of IL-6, a secondary proinflammatory cytokine, which in turn stimulates the

production of acute-phase proteins by the liver 7. Examples of these proteins include C-

reactive protein and fibrinogen 7.

IL-1 and TNF are also crucially important in mediating the infiltration of tissue by

leukocytes, via the initial induction of leukocyte adhesion molecules such vascular cell

adhesion molecule-1 (VCAM-1), intercellular cell adhesion molecule-1 (ICAM-1) and E-

selectin on endothelial cells 8. The induction of adhesion molecules by these cytokines

Figure 1. Illustration of the cellular kinetics and sequential release of mediators during the evolution of the inflammatory response. (Adapted from Lawrence, T. and Gilroy, D.W., 2007)

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allows for the adhesion of leukocytes to endothelial cells 9. The endothelium retracts,

allowing for the migration of the transiently adhered leukocytes into the inflamed tissue in

response to chemoattractant cytokines that are also induced by IL-1 and TNF 9.

Interleukin 1

Interleukin-1 is a glycoprotein that exists in two major biologically active forms, IL-1� and

IL-1� 10. These two functionally similar molecules, IL-1� and IL-1�, are encoded by

separate genes (respectively, IL1A and IL1B) 10. Of these, IL-1� is the predominant

circulating isoform in humans. IL-1� and IL-1� have undistinguishable functions and their

pro-inflammatory effects are numerous on most cell types. However, IL-1� is a secreted

protein, while IL-1� is mainly a cell-associated molecule 11. The main sources of IL-1 are

stimulated blood monocytes and tissue macrophages, and IL-1� is also present in the

hypothalamus 6. A recent study demonstrates that expression of IL1� is increased in both

obese rodents and humans 12.

Interleukin-1 plays an important role in the regulation of the inflammatory response.

Indeed, this primary inflammatory cytokine has been implicated in mediating both acute

and chronic pathological inflammatory diseases 13.The actions of IL-1 appear to be

mediated by a relatively well-known biochemical pathway. IL-1 binds to the type1 IL-1

receptor-associated protein, then binds to the complex, initiating intracellular signalling

pathways, such as the �� kinase pathway, or those involving various small GTPases 14.

This results in the activation of transcription factors that in turn increases the expression of

proinflammatory genes encoding chemokines, cytokines, acute-phase proteins, cell

adhesion molecules, degradative metalloproteinases, and other enzymes 14. Indeed,

administration of IL-1 to humans induces the release of secondary cytokines such as IL-6

and IL-8 15.

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A polymorphism (C/T) was described at the position -511 in the promoter region of the

human IL-1� gene 16, and T allele showed a modest increase in transcriptional activity

when compared with C allele 17 18 19.

Tumor necrosis factor

Originally described by its antitumor activity, tumor necrosis factor alpha (TNF�) is now

recognized as a cytokine with multiple biological capacities. The cytokine TNF� is a non-

glycosylated protein acting as modulator of gene expression in adipocytes and is

implicated in the development of insulin resistance and obesity 20. Fat tissue is a

significant source of endogenous TNF� production, and the expression of this cytokine is

elevated in human obesity in adipose tissue 20. An earlier study 21 demonstrated that

adipocytes constitutively express the proinflammatory cytokine TNF and that TNF

expression in adipocytes of obese animals (ob/ob mouse, db/db mouse and fa/fa Zucker

rat) is markedly increased. These observations provided the link between an increase in

the expression and the plasma concentration of a proinflammatory cytokine and insulin

resistance. Monocytes and macrophages are the main producers of TNF�, but other cells

such as T-lymphocytes, natural killer cells, smooth muscle cells, endothelial cells and

some tumour cells also produce TNF� 22.

TNF� is a powerful local regulator within adipose tissue, acting in both an autocrine and a

paracrine manner to influence a range of processes, including apoptosis 23 24. There

appears to be a hierarchy of cytokines within fat, with TNF playing a pivotal role in relation

to the production of several cytokines and other adipokines 24. TNF� stimulates cellular

kinase complex known as I Kappa B Kinase (IKK), which activates nuclear factor (NF)-��,

a transcription factor that, in turn, drives the production of proinflammatory cytokines

including IL-1�, IL-6, TNF and interferon 25.

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Linkage analysis has shown that a marker near the TNF� region on chromosome 6 was

significantly linked with obesity in Pima Indians 26. The gene for human TNF� is located on

the short arm of chromosome 6 and a G-A substitution at position -308 upstream from the

transcription initiation site in the promoter region of the gene has been identified 27. In vitro

experiments have demonstrated that this substitution increases transcriptional activation

of the TNF� gene 28. Although controversial, the majority of the data support a direct role

for this biallelic polymorphism in the elevated TNF� levels observed in homozygotes for

the -308A allele 29.

Interleukin 6

Interleukin-6 (IL-6) is an acute-phase response cytokine produced by many different cell

types, including immune and endothelial cells, fibroblasts, myocytes, and adipocytes 30.

Fat mass has been implied as a major source for circulating IL-6, with visceral fat

producing higher levels of IL-6 compared with subcutaneous fat 31. In obese subjects with

high waist-to-hip ratio, the participation is even greater 32.

It regulates humoral and cellular responses and plays a central role in inflammation and

tissue injury 33. IL-6 is one of the main inducers of the hepatic synthesis and secretion of C

- reactive protein (CRP) in response to infection or inflammation 34. It has been proposed

that IL-6 has direct central actions on the control of fat mass, as IL-6 receptors were found

in hypothalamus in mice 32 35, and as it was found a negative correlation between the

concentration of IL-6 in the cerebrospinal fluid and the fat mass, in obese subjects 36.

A polymorphism (G/C) at the position -174 in the promoter region of the human IL-6 gene

was described 37 and suppression of IL-6 transcription 37 38 resulted from this single

nucleotide change from G to C.

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C-reactive protein

C-reactive protein is an ancient, highly conserved molecule and consists of five identical,

non-glycosylated peptide subunits linked to form a cyclic polymerase 39. CRP is an acute

phase reactant synthetized and secreted by the liver in response to a variety of

inflammatory cytokines, increases rapidly in response to trauma, inflammation, and

infection and decreases just as rapidly with the resolution of the condition 40. Thus, the

measurement of CRP can be used to monitor inflammatory states. The development of

high sensitivity assays for CRP has enabled the detection of mild elevation of CRP within

the normal range 41. The application of these assays during the last years has made it

possible to study CRP in a wide variety of inflammatory diseases, being the most

commonly used and best standardized inflammatory marker of cardiovascular and

metabolic disorders 41 42.

CRP has a role in the function of the innate immune system. It activates complement,

binds to Fc receptors, and acts as an opsonin for various pathogens 43. Binding of CRP to

Fc receptors leads to generation of proinflammatory cytokines 43. CRP can recognize

altered self and foreign molecules based on pattern recognition 43. Thus, enhanced levels

of CRP can be used as a marker of inflammation.

Fibrinogen

Fibrinogen, a glycoprotein dimmer composed of three pairs of non-identical polypeptide

chains (alpha, beta and gamma) 44 linked to each other by disulphide bonds, is a key

coagulation factor and acute phase reactant exclusively synthesized by the liver 39 and is

inducible by IL-6 as part of the acute phase reaction 45. Fibrinogen has a plasma half-life

of 3–5 days and is a key plasma protein 44. At the final step of the coagulation cascade, it

is transformed into fibrin under the action of thrombin 44. Fibrinogen binding to the

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GPIIb/IIIa receptor in activated platelets is the key step in platelet aggregation 46.

Furthermore, fibrinogen is the major determinant of plasma viscosity and erythrocyte

aggregation and, therefore, affects blood viscosity both at high shear rate (primarily

relevant for flow in arteries, arterioles, and capillaries) and low shear rate (relevant for flow

in veins and under stasis) 47.

Fibrinogen is a ligand for ICAM-1, that behaves as a cell surface ligand for a few integrins,

and enhances monocyte-endothelial cell interaction 48. Fibrinogen upregulates and

increases the concentration of ICAM-1 proteins on the surface of endothelial cells,

resulting in increased adhesion of leukocytes, platelets and macrophages on the surface

of endothelial cells 49.

Leucocytes

Leukocytes, also called white blood cells, can be categorized into three main groups,

neutrophils, monocytes/macrophages, and lymphocytes 50. Leukocyte recruitment is

necessary for host defense against infection and for normal wound healing 51. Neutrophils,

or polymorphonuclear leukocytes (PMNs), are the most common leukocyte in humans,

numbering ~5 × 106 per milliliter of blood 51. Their recruitment and subsequent

transmigration into inflamed tissue is the earliest cell adhesion event following tissue

insult, and this occurs in virtually every organ 51.

Molecular specificity in the targeting of leukocytes at sites of inflammation 52 is mediated

by selectins, integrins, and the immunolglobulin gene superfamily. In the surrounding

tissue of the inflammation site, the chemoattractants released trigger a complicated

cascade, which results in the migration of circulating leukocytes towards the site of

inflammation (chemotaxis) 53. This is a well coordinated process involving first the

attraction of polymorphmononuclear leukocytes, followed by the activation and adhesion

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of these cells to the endothelium of the blood vessel (margination) and finally, diapedesis

(infiltration) into the extravascular space and migration to the site of inflammation 53.

Uric Acid

Uric acid is the main end product of metabolism of purines, which in turn are derived

mostly from diet, de novo biosynthesis, and breakdown of nucleic acids 54. Serum uric

acid levels, therefore, increase with higher protein intake, increased endogenous

production of urate, or decreased excretion of monosodium urate by kidneys 54. In most

mammals, uric acid is degraded by the hepatic enzyme uricase to allantoin 55. However,

mutations in the uricase gene occurred during primate development, with the

consequence that humans have relatively higher levels of serum uric acid 56. Elevated

levels of uric acid correlate with aging, male gender, hyperlipidemia, obesity,

hyperinsulinemia, diabetes mellitus, and glucose intolerance 57 58.

Uric acid activates the complement system 59, and in soluble form induces the

development of oxidative stress and LDL oxidation 59. It is proinflammatory in rat vascular

smooth muscle cells and stimulates human mononuclear cells to produce cytokines 60 61. It

also stimulates the inflammatory response by increasing the production of the chemotactic

factor monocyte chemoattractant protein-1 (MCP-1) in vascular smooth muscle cells and

CRP synthesis in human vascular endothelial and smooth muscle cells 62 63.

Hyperuricemic rats have a significant increase in macrophage infiltration in their kidneys

independent of crystal deposition 55.

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OBESITY

The World Health Organisation (WHO) defines obesity as “an abnormal or excessive fat

accumulation in adipose tissue, to the extent that health is impaired” 64. The currently

accepted classification of adult obesity for epidemiological purposes defines overweight at

body mass index (BMI) levels greater than 25 kg/m2 and obesity beginning at BMI of 30

kg/m2 64. Worldwide 1.1 billion people are currently estimated to be overweight, at least

300 million of them obese 64. Obesity is an epidemic, affecting all races, with high

incidence, mainly, in the western societies 65 and with increasing prevalence among

Portuguese people 66. It is associated with the incidence of several adverse health

problems, including diabetes mellitus, cardiovascular disease, hypertension and cancer 67.

It was previously reported that obesity is more strongly linked to chronic diseases than

living in poverty, smoking, or drinking 68.

Obesity is not a single disorder but a heterogeneous group of conditions with multiple

causes. Body weight is determined by an interaction between genetic, environmental and

psychosocial factors acting through the physiological mediators of energy intake and

expenditure 69.

Figure 2. Factors influencing the development of obesity (Kopelman, P.G., 2000)

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Obesity is characterized by an expanded fat mass that, in the past, was mainly seen as a

storage organ 70, being recently recognized as functionally comparable to an endocrine

organ, producing and secreting various adipokines, such as leptin and adiponectin, and

cytokines such as tumor necrosis factor � (TNF-�), interleukin-6 and interleukin 1 11. TNF-

�, IL-6 and IL-1 are classical pro-inflammatory cytokines inducing both acute and chronic

inflammatory responses 11, with a potential role in obesity and obesity complications 21. In

recent years, evidence indicates that chronic low-grade activation of the immune system

plays an important role in the aetiology of obesity and related metabolic dysfunctions 12.

The different anatomic location of adipose tissue accumulation plays an important role in

the development of obesity related co-morbidities. Upper body fat includes the visceral

and abdominal subcutaneous depots 71. The visceral fat depot is contained within the

body cavity, surrounding the internal organs, and is composed of the mesenteric and the

greater and lesser omental depots 71. Visceral depots represent 20 and 6% of total body

fat in men and women, respectively 72. The abdominal subcutaneous fat depot is situated

immediately below the skin in the abdominal region 71. In the lower body, all adipose

depots are subcutaneous with the two larger sites of storage in the gluteal and femoral

regions 71.

Not all fat is created equal: cells in some parts of the body may pump out more of the

molecular signals that promote obesity-related disease 73. Visceral fat, which can affect

both the lean and obese, seems to be particularly problematic because it dumps signalling

molecules directly into blood heading for the liver, the main site where glucose and fat are

converted from one to another 73. Subcutaneous fat, seems to be less metabolically active

and therefore may produce less of these molecules 73. Individuals with comparable

amounts of fat stored in the femoral or gluteal depots (lower body obesity) have a much

lower risk of morbidity from metabolic disturbances 71.

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OBESITY AND INFLAMMATION

The origin of systemic inflammation in metabolic obesity has been subject of debate in

recent years and evidence is accumulating that adipose mass plays a major role in

production of cytokines like interleukin-1, interleukin-6 and tumour necrosis factor alpha 74.

Over the past decade it has become clear that fat cells send out distress signals that can

promote insulin resistance and trigger inflammation 21, which may, in turn, cause type 2

diabetes, cardiovascular disease, increased cancer risk and other obesity-associated

problems 73.

It was described that adipocyte precursors have potent phagocytic capacity and can be

transformed into macrophage-like cells in response to appropriate stimuli 75. Experiments

in mice bone marrow chimeras have demonstrated that adipose mass macrophages are

bone marrow derived, indicating that macrophages present in adipose tissue do not derive

in situ from differentiation of preadipocytes but rather from circulating monocytes

infiltrating fat mass76. Despite the different results, it appears that obesity is associated

with a low-grade inflammation characterized by increased macrophage infiltration 76. This

infiltration increases in proportion to BMI and to adipocyte hypertrophy 31. Activated

macrophages contribute to a downward spiral of inflammation, releasing cytokines and

biologically active molecules such as TNF�, IL-6, and IL-1 30. In turn, these molecules

increase production of acute-phase proteins.

These data may suggest that once inflammatory trigger is established in adipose tissue

with increasing macrophage infiltration and increased cytokines, a self perpetuating

mechanism develops. However, remains unclear what triggers macrophage infiltration.

One recent study reports that >90% of macrophages in white adipose tissue of obese

mice and humans are localized to dead adipocytes 77. It is postulated that adipocyte

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hypertrophy promotes adipocyte death, macrophage aggregation and adipose tissue

inflammation.

Several inflammatory cytokines are now recognized to be expressed in, and secreted by,

white adipocytes. The first to be identified was TNF�, whose expression was initially

demonstrated in rodents and found to be markedly increased in obese models 21. As well

IL6 and IL1 were found to be present in fat mass 1 31 32. The production of a cytokine is

influenced by single base changes (single nucleotide polymorphisms), usually in the

promoter region of its gene 78. Therefore, individuals may have a genetically determined

propensity for raised amount of cytokine production and, consequently, for higher

production of acute phase proteins. The possibility of an inter-individual and genetically

determined difference in basal and post-stimulus of IL1, IL6 and TNF levels suggested

that these polymorphisms may play a role in the regulation of inflammatory processes and

synthesis of acute-phase reactants. Given that cytokine gene polymorphisms have been

shown to be involved in the susceptibility, clinical performance, and outcome in a variety

of diseases 79, exploration of the genetic relationship between proinflammatory cytokine

polymorphisms and adiposity has significant implications for understanding the

pathogenesis of obesity. To observe this effect on inflammation, we used four

inflammatory markers, C-reactive protein, leukocytes, fibrinogen and uric acid. The basal

values of CRP and white blood cell appear to be significantly heritable (� 40%) 80, and

therefore it is very likely that polymorphisms in genes controlling inflammatory markers

expression may influence their levels, as well as for fibrinogen and uric acid.

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AIMS

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AIMS

In the sense of studying the influence of fat distribution in the inflammatory outcome

phenotype of specific polymorphisms affecting genes enconding pro-inflammatory

cytokines, the aims of this study are:

- To identify the prevalence of the polymorphisms in the study group;

- To analyse if there is an association between the polymorphisms and obesity;

- To assess whether polymorphisms in genes coding for IL-6, TNF� and IL-1� influence

inflammatory markers levels;

- To evaluate the interaction between the study polymorphisms and fat distribution in

relation to inflammatory markers concentrations.

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PARTICIPANTS AND METHODS

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PARTICIPANTS AND METHODS

Participants

Participants were selected as part of a population based health and nutrition survey

previously described in detail 81. Non-institutionalized inhabitants of Porto, Portugal, were

selected using random digit dialing. After the identification of a household, permanent

residents were characterized according to age and sex, and one adult was selected by

simple random sampling and invited to visit our department for interview and examination.

If there was a refusal, replacement was not allowed. The participation rate was 70% 81. As

part of the ongoing cohort study, we revaluated a convenient sample of 359 individuals.

The local institutional ethics committee approved the study and all participants gave

written informed consent.

Trained interviewers collected information using a structured questionnaire. Data on

social, demographic, personal and family medical history and behavioral characteristics

were obtained as self-reported.

Anthropometric measurements

Anthropometrics were obtained after 12 h fasting, the participant in light clothing and no

footwear. Body weight was measured to the nearest 0.1 kg using a digital scale, and

height to the nearest centimeter in the standing position using a wall stadiometer. Body

mass index (BMI) was calculated as weight in kilograms divided by square height in

meters.

Waist and hip circumferences were measured to the nearest centimeter, with the subject

standing, with a flexible and non-distensible tape, avoiding exertion of pressure on the

tissues. Waist circumference (WC) was measured midway between the lower limit of the

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Joana Barroso

rib cage and the iliac crest, hip circumference was the maximal circumference over the

femoral trochanters, and the waist to hip circumference ratio (WHR) was calculated.

Waist circumference and WHR were used to analyze the effect of the interaction between

the IL6 -174G/C polymorphism and abdominal adiposity in CRP levels. Fat mass was

obtained by bioelectrical impedance analysis.

Measurement of CRP plasma levels

Blood was drawn after a 12 hour overnight fast. High sensitivity C-reactive protein levels

were determined by means of particle-enhanced immunonephelometry using a BNTM II

nephelometer (Dade Bhering). For the purpose of this study, we evaluated 359

participants, of whom we excluded 37 (10.3%) for CRP analysis because they presented

CRP levels above 10mg/L, which might indicate clinically relevant inflammatory

conditions41 82.

Uric acid and fibrinogen concentration was assessed by a standard colorimetric enzymatic

assay.

Leukocytes count was measured by flux citometry, using an automatic hematologic

counter Sysmex® XE-2100.

Genotyping

Genomic DNA was retrieved from blood samples using standard proteinase K digestion

and phenol/chloroform extraction. The G/C single nucleotide polymorphism at position -

174 of the interleukin-6 gene and the C/T single nucleotide polymorphism at position -511

of the interleukin 1 � were performed by polymerase chain reaction (PCR) amplification,

using the following primer pairs:

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Joana Barroso

IL6 Primer forward 5’ GCCTCAATGACGACCTAAGC 3’

IL6 Primer reverse 5’ AATGTGGGATTTTCCCATGA 3’

IL1 � Primer forward 5’ GCCTGAACCCTGCATACCGT 3’

IL1� Primer reverse 5’ GCCAATAGCCCTCCCTGTCT 3’

The reaction was carried out in a final volume of 25µL, containing 200µmol/L each dNTP,

20pmol each primer, 50mmol/L of KCl, 10mmol/L Tris-HCL (pH 9.0), 1.5mmol/L of MgCl2

and 1U Taq polymerase (Amershan Biosciences, New Jersey). DNA was amplified during

35 cycles with an initial denaturation of 30 seconds at 94ºC, a 30 seconds annealing at

58ºC and an extension of 30 seconds at 72ºC.

PCR products were digested with 5U restriction enzyme Aval (MBI, Fermentas) and buffer

Y+/Tango 1x (33mM Tris-acetate, 10mM magnesium acetate, 66mM potassium acetate,

0.1mg/mg BSA) at 37ºC overnight and separated by electrophoresis on a 1.5% agarose

gel stained with ethidium bromide. PCR products were sized relative to a 1-kilobase

ladder. The IL6 alleles were designated as follows: G allele with 2 bands of 110 and 49

bp, C allele with a single band of 164 bp, and the C/G allele with 3 bands of 164, 110 and

49 bp.

The IL1 alleles were designated as follows: C allele with 2 bands of 90 and 65 bp, T allele

with a single band of 155 bp, and the C/T allele with 3 bands of 155, 90 and 65 bp.

The G/A single nucleotide polymorphism at position -308 of the tumour necrosis factor-�

gene was performed by TaqMan system (ABI Prism 7000 Sequence Detection System,

Applied Biosystems, using assays-on-demand, from Applied Biosystems (C_7514879,

C_11918223_10, respectively). For each genotyped individual we used TaqMan Universal

Master Mix 1x and assay-on-demand 1x, with a total volume of 11µL. DNA was amplified

during 40 cycles of 15 seconds at 95ºC and 60 seconds at 60ºC. Allelic discrimination was

performed during 60 seconds at 60ºC.

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Joana Barroso

Statistical Methods

Chi-square analysis was used to determine if genotype frequencies were in Hardy-

Weinberg equilibrium. Differences in sex distribution between genotypes were evaluated

by Pearson Chi-square. Characteristics were tested for differences between genotypes

using ANOVA for continuous variables (age, body weight, BMI, waist, hip, WHR, fat mass,

free fat mass).

Linear regression was used to adjust outcome for age and gender, according to allele.

Due to CRP non-normally distributed data, we used Box Cox transformation to convert it

to a normal distribution. To assess the effect of polymorphisms in inflammatory markers

levels and to observe if there was an interaction between the polymorphisms and WC and

WHR with any effect in inflammatory markers levels, we used univariate analysis of

variance. Spearman’s rho was used to evaluate the correlation between CRP plasma

levels and body weight, BMI, waist and hip circumferences, WHR, fat mass, free fat mass.

Pearson correlation was used to evaluate the correlation between leukocyte, fibrinogen

and uric acid levels and obesity indices.

To evaluate the correlation between inflammatory markers we used spearman’s � and

pearson correlation.

Levels of statistical significance were set at p < 0.05.

Data were analyzed using SPSS software (version 14.0.0) and R software (version 2.6.0).

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CHAPTER I

IL-6 -174G/C POLYMORPHISM INTERACTS WITH ABDOMINAL ADIPOSITY TO INCREASE C-REACTIVE PROTEIN

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RESULTS

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RESULTS

Genotyping of the IL-6 -174 G/C polymorphism was performed for 322 subjects (215

women and 107 men). There were 144 (44.7%) participants with GG genotype, 132

(41.0%) GC heterozygotes, and 46 (14.3%) CC homozygotes. Genotype and allele

proportions were in Hardy Weinberg equilibrium (X2= 2.98; p=0.225).

The relative frequency of -174C allele was 0.35. Main characteristics of the study

population, according to genotype are presented in table 1.

Table 1. Subjects’ characteristics according to the -174G/C genotype

G/G G/C C/C P2

n (%) 144(44.7) 132 (41.0) 46 (14.3) ---

Gender

Male n(%)

Female n(%)

49 (34.0)

95 (66.0)

39 (29.5)

93 (70.5)

19 (41.3)

27 (58.7)

0.333

Age (years)1 56.9±15.20 56.4±14.76 57.4±17.21 0.920

Body weight (kg)1 69.9±15.32 72.1±13.70 73.2±13.02 0.279

BMI (kg/m2)1 27.1±5.15 28.9±5.87 28.2±4.49 0.028

Waist (cm)1 91.6±13.59 93.8±13.19 95.4±11.17 0.156

Hip (cm)1 101.4±9.03 104.4±10.78 103.7±8.20 0.034

WHR1 0.9±0.08 0.9±0.08 0.9±0.06 0.283

Fat Mass (kg)1 21.8±9.43 24.3±10.28 23.2±8.31 0.095

1 Results are expressed as mean ± SD. 2 ANOVA BMI, body mass index; WHR, waist-hip ratio.

When we evaluated markers of obesity, according to -174 G/C genotype, we found

significant differences for BMI (p=0.028) and hip circumference (p=0.034), with people

carrying the rare C allele presenting higher mean values than GG homozygotes.

When comparing GG homozygotes with C carriers, after adjusting for age and gender, C

carriers’ BMI (�=1.572, p=0.006) and hip circumference (�=2.825, p=0.007) mean values

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Joana Barroso

remained significantly higher as was the case for mean waist circumference (�=2.795,

p=0.036) and fat mass (�=2.195, p=0.030) (table 2).

Table 2. Subjects’ characteristics according to allele, adjusted for age and gender

C carrier1 G carrier2

�3 P4 �

3 P4

Body weight (kg) 2.661 0.079 -1.217 0.574

BMI (kg/m2) 1.572 0.006 -0.293 0.720

Waist (cm) 2.795 0.036 -2.071 0.277

Hip (cm) 2.825 0.007 -1.065 0.478

WHR 0.004 0.620 -0.011 0.284

Fat Mass (kg) 2.195 0.030 -0.655 0.654

BMI, body mass index; WHR, waist-hip ratio. 1 Reference class - homozygotes G/G 2 Reference class - homozygotes C/C 3 Values were calculated by linear regression. 4 P value adjusted for age and gender.

CRP was significantly correlated with body weight (Spearman’s rho=0.150, p<0.001), BMI

(Spearman’s rho=0.303, p<0.001), waist (Spearman’s rho=0.242, p<0.001) and hip

circumference (Spearman’s rho=0.259, p<0.001), WHR (Spearman’s rho=0.102, p<0.001)

and fat mass (Spearman’s rho=0.316, p<0.001).

CRP plasma levels were not significantly different according to genotypes, when

comparing homozigotes GG with heterozigotes GC (�=0.055, p=0.673) and homozigotes

CC (�=-0.066, p=0.718).

To evaluate if there was an interaction between IL6 -174C/G polymorphism and

abdominal fat in relation to CRP levels, individuals were evaluated according to WC and

WHR. It was found a significant association between waist circumference and C carriers –

GC (�=0.039, p<0.001) and CC (�=0.037, p=0.006), meaning that for people with equal

values of waist circumference, C carriers have higher CRP levels than homozigotes GG

(table 3). This association remained statistically significant even after adjustment for

gender, age and smoking habits (table 3).

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Joana Barroso

In relation to WHR, significant association was found with heterozigotes GC, which

showed higher CRP levels than homozigotes GG (table 3). No significant difference was

seen between CRP levels for homozigotes CC and homozigotes GG (table 3).

Table 3. The effect of IL6 -174G/C polymorphism in the association between waist circumference and waist-to-hip ratio with CRP

Crude Adjusted*

IL6 -174 G/C WC WCxGC WCxCC WC WCxGC WCxCC

� -0.001 0.039 0.037 -0.001 0.038 0.033

p 0.382 <0.001 0.006 0.478 <0.001 0.015

IL6 -174 G/C WHR WHRxGC WHRxCC WHR WHRxGC WHRxCC

� 0.499 4.151 1.828 1.193 4.502 1.506

p 0.635 0.010 0.502 0.306 0.004 0.578

WC, waist circumference; WHR, waist to hip ratio. *Adjusted for age, gender, smoking habits and the main effect of the polymorphism.

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DISCUSSION

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DISCUSSION

It is well recognized that genetic polymorphisms in susceptibility genes may modulate the

response to an inflammatory stimulus and that CRP is subjected to genetic modulation83.

Considering the association between IL-6 genetic variants and abdominal fat, as well as

the association between the latter and C-reactive protein plasma levels, we might

speculate that a possible interaction between the -174G/C polymorphism and abdominal

fat could be one of the reasons for the controversial results observed in studies that

evaluated the effect of the polymorphism on CRP levels.

Therefore, we genotyped 322 individuals, of whom 44.7% were GG homozygotes, 41.0%

were heterozygotes and 14.3% were CC homozygotes. The frequency of the -174C allele

was 0.35, which is close to other European Caucasian populations37 84.

Once we compared subjects’ characteristics according to IL-6 -174G/C genotype,

significant differences were shown for BMI, with C carriers presenting higher mean values,

as previously seen in a study with two populations, one consisting of hypertensive

individuals and other consisting of 20 year younger nonobese healthy females85. The -

174C allele seems to be associated with lower IL-6 transcription37 86 and there is clear

evidence from experimental studies that endogenous IL-6 suppresses body fat mass and

prevents late-onset obesity35. Recent studies indicate that -174C allele is associated with

decrease energy expenditure87. Taken together, these results indicate that -174C allele

decreases IL-6 production, which in turn results in decreased energy expenditure and

accumulation of body fat.

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Joana Barroso

Furthermore, we evaluated subjects’ characteristics according to genotype in a dominant

(GG vs CG+CC) and recessive (CC vs CG+GG) models. C carriers were associated with

higher values of obesity markers, such as BMI, waist and hip circumference and fat mass.

A study of 270 non-smoking men free from metabolic disorders, showed a significant

effect of the IL-6 polymorphism on obesity, the -174G allele being more common among

lean subjects (low BMI)88. Also, GG homozygotes presented a significantly smaller waist

circumference and -174C allele carriers a larger waist line88. These results fit well with the

finding of a lower basal metabolic rate in CC homozygotes87, associating this genotype

with higher indices of obesity and obesity markers. Waist to hip ratio and body weight

were the only obesity parameters that showed no significant association with IL-6 -

174G/C.

We confirmed the known positive association between CRP levels and BMI89 90, also

present with other obesity markers91 92. CRP levels were strongly positive correlated with

waist circumference, demonstrating that as larger is the waist line, the higher are CRP

levels. WC is a strong correlate of visceral fat93, and elevated CRP concentration may

reflect cytokine production by visceral adipocytes, because IL-6 and CRP levels are

closely related with visceral fat94. A prior study with 190 overweight subjects has also

shown association between waist circumference and CRP levels95.

Even though we cannot discard the possibility that the IL-6 -174G/C polymorphism alone

could influence CRP plasmatic levels, we found no significant differences among the three

genotypes. Other studies also found no statistically significant differences in CRP levels

between genotypes96 97. It is possible that this IL-6 polymorphism has none or only modest

effects on CRP induction when expressed alone. As shown in a study using IL-6-deficient

mice, it was demonstrated that injection of IL-6 is not sufficient for induced expression of

CRP gene98. In fact, these effects might be expressed only in the presence of other

factors99. Combined results have established that IL-6 is the principal inducer of the CRP

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Joana Barroso

gene, while IL-1, glucocorticoids and other factors, including complement activation

products, act synergistically with IL-6 43. In this sense, we might hypothesize that the

interaction with WC could be responsible for the different results described on the impact

IL6 -174G/C polymorphism on CRP in humans.

Möhlig et al. demonstrated a similar interaction between -174G/C polymorphism and BMI,

in relation to IL6, an inflammatory marker as well 100. In their study, increased BMI was

correlated with higher IL-6 concentrations for the CC genotype than for GG genotype100.

Effect modification between a genotype and an environmental factor is a scientifically

important model. Therefore, we assessed a possible interaction between the

polymorphism and abdominal adiposity within CRP levels. For the GC and CC genotype,

WC is associated with higher CRP levels, when compared with homozigotes GG. These

data demonstrate a gene-environment interaction that may help explain the controversial

results described in the literature concerning the effect of the polymorphism in CRP

concentrations. The mechanisms by which the C allele and WC could cause an increased

in CRP levels are unknown, but this allele might act as a triggering agent of the dose-

dependent lipolytic effect of IL6 on peripheral storages 101 driving to fat mobilization toward

the abdominal compartment, which in turn is a source of pro-inflammatory cytokines11 that

stimulate the hepatic secretion of CRP. On the other hand, a putative synergistic effect

between abdominal fat and IL6 polymorphism regarding CRP levels is possible, as both

factors have been described as influencing IL6 concentrations31 37 86 and consequently

CRP levels, given that IL6 is the main inducer of hepatic secretion of this acute-phase

protein34.

To the best of our knowledge, no other study tried to evaluate the interaction between IL-6

polymorphism and abdominal adiposity within CRP levels and although we observed an

interaction, in epidemiological studies, like this one, we cannot elucidate the mechanisms

responsible for the interactions described. Thus, which factors linked to WC and IL6 gene

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Joana Barroso

expression dependent on the -174G/C polymorphism differentially regulate CRP remain to

be evaluated.

Our sample is neither ethnically diverse nor nationally representative, and is uncertain

how our results would apply to other ethnic groups. However, in genetics studies, sample

homogeneity is beneficial in order to reduce population stratification. Not having a direct

measure of visceral adiposity is also a limitation of this study, although waist

circumference was shown as a good surrogate for visceral adiposity102. Further

investigation using other techniques to measure fat distribution may provide new insights

to understand that association.

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CHAPTER II

IL6, IL1�ETA AND TNF�LFA GENOTYPE AND FAT DISTRIBUTION: EFFECT ON INFLAMMATORY MARKERS

44

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RESULTS

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Joana Barroso

RESULTS

We evaluated three polymorphisms (IL6 -174G/C; IL1� -511C/T; TNF� -308G/A) encoding

for transcription of pro-inflammatory proteins and their association with four inflammatory

markers (C-reactive protein; uric acid; leukocytes and fibrinogen).

We found a strong positive correlation between the four inflammatory markers (table 1),

with the exception of uric acid and fibrinogen.

Table 1. Correlation between the four inflammatory markers

C-reactive Protein (mg/L)

Leukocytes (x109/L)

Uric Acid (mg/L)

Spearman’s � p Pearson

Correlation p Pearson Correlation p

Leukocytes (x109/L) 0.240 <0.001 ------ ------

Uric Acid (mg/L) 0.103 <0.001 0.110 <0.001 ------ ------

Fibrinogen (g/L) 0.441 <0.001 0.181 <0.001 -0.010 0.742

C-reactive protein showed strong correlation with body weight (Spearman’s rho=0.150,

p<0.001), BMI (Spearman’s rho=0.303, p<0.001), waist (Spearman’s rho=0.242, p<0.001)

and hip circumference (Spearman’s rho=0.259, p<0.001), waist-hip ratio (Spearman’s

rho=0.102, p<0.001) and fat mass (Spearman’s rho=0.316, p<0.001) (table 2).

Leukocytes showed correlation with body weight (Pearson correlation=0.063, p=0.022),

waist circumference (Pearson correlation=0.084, p=0.002), waist-hip ratio (Pearson

correlation=0.117, p<0.001) and free fat mass (Pearson correlation=0.058, p=0.037)

(table 2).

Uric acid was correlated with all obesity markers, body weight (Pearson correlation=0.441,

p<0.001), BMI (Pearson correlation=0.283, p<0.001), waist (Pearson correlation=0.434,

p<0.001) and hip circumference (Pearson correlation=0.201, p<0.001), waist-hip ratio

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Joana Barroso

(Pearson correlation=0.461, p<0.001), fat mass (Pearson correlation=0.205, p<0.001) and

free fat mass (Pearson correlation=0.458, p<0.001) (table 2).

Fibrinogen demonstrated correlation with BMI (Pearson correlation=0.112, p<0.001), hip

circumference (Pearson correlation=0.093, p=0.003), fat mass (Pearson

correlation=0.123, p<0.001) and free fat mass (Pearson correlation=-0.188, p<0.001)

(table 2).

Table 2. Association between inflammatory markers and obesity indices

BMI, body mass index; WHR, waist-hip ratio.

In relation to IL6 -174G/C polymorphism, we previously saw that people carrying the C

allele had higher BMI and hip circumference, and after adjustment for age and gender,

they showed higher waist circumference and fat mass. We also noticed that CRP plasma

levels were not significantly different according to genotypes, when comparing

homozigotes GG with heterozigotes GC, but when we evaluated the interaction between

WC and IL6 polymorphism, there was a significant association between waist

circumference and C carriers, with heterozigotes GC and homozigotes CC presenting

higher CRP levels than homozigotes GG.

Leukocytes levels revealed no significant differences when comparing homozigotes GG

with heterozigotes GC (�=0.271, p=0.138) and homozigotes CC (�=0.228, p=0.382).

C-reactive Protein (mg/L)

Leukocytes (x109/L)

Uric Acid (mg/L)

Fibrinogen (g/L)

Spearman’s � p Pearson

Correlation p Pearson Correlation p Pearson

Correlation p

Body weight (kg) 0.150 <0.001 0.063 0.022 0.441 <0.001 -0.052 0.100

BMI (kg/m2) 0.303 <0.001 0.053 0.052 0.283 <0.001 0.112 <0.001

Waist (cm) 0.242 <0.001 0.084 0.002 0.434 <0.001 0.050 0.113

Hip (cm) 0.259 <0.001 0.014 0.619 0.201 <0.001 0.093 0.003

WHR 0.102 <0.001 0.117 <0.001 0.461 <0.001 -0.024 0.451

Fat Mass (kg) 0.316 <0.001 0.033 0.238 0.205 <0.001 0.123 <0.001

Free Fat Mass (kg) -0.047 0.091 0.058 0.037 0.458 <0.001 -0.188 <0.001

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Joana Barroso

It was found no interaction between waist circumference and C carriers. This association

became statistically significant after adjustment for gender, age and smoking habits when

comparing GG homozigotes with heterozigotes GC (�=0.022, p=0.018) and with

homozigotes CC (�=0.045, p=0.020) (tabela 3).

In relation to WHR, no significant association was found (table 3).

Table 3. The effect of IL6 -174G/C polymorphism in the association between waist circumference and waist-to-hip ratio

with leukocytes

Crude Adjusted*


� 0.001 0.012 0.037 0.002 0.022 0.045

p 0.400 0.225 0.062 0.178 0.018 0.020


� -0.187 2.552 4.239 1.310 2.184 5.034

p 0.903 0.264 0.285 0.438 0.321 0.197


Uric acid levels revealed no significant differences when comparing homozigotes GG with

heterozigotes GC (�=0.739, p=0.675) and homozigotes CC (�=1.430, p=0.569).

It was found a significant association between waist circumference and C carriers – GC

(�=0.392, p<0.001) and CC (�=0.485, p=0.007), meaning that for people with equal

values of waist circumference, C carriers have higher CRP levels than homozigotes GG

(table 4). This association remained statistically significant even after adjustment for

gender, age and smoking habits (table 4).


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Joana Barroso


with uric acid

Crude Adjusted*


� 0.048 0.392 0.485 0.031 0.349 0.398

p 0.003 <0.001 0.007 0.027 <0.001 0.014


� 96.550 -21.560 19.700 58.795 -15.792 19.031

p <0.001 0.270 0.560 <0.001 0.398 0.564


Fibrinogen levels revealed no significant differences when comparing homozigotes GG

with heterozigotes GC (�=0.169, p=0.109) and homozigotes CC (�=0.137, p=0.334).

It was found a significant association between waist circumference and homozigotes GG

(�=-0.002, p=0.015) and GC genotype (�=0.016, p=0.006) (table 5). This association

remained statistically significant even after adjustment for gender, age and smoking habits

(table 5).



with fibrinogen

Crude Adjusted*


� -0.002 0.016 0.012 -0.002 0.015 0.012

p 0.015 0.006 0.270 0.013 0.013 0.244


� -0.117 2.356 1.984 -0.259 2.504 1.488

p 0.903 0.090 0.373 0.807 0.069 0.509


Genotyping of the IL1� -511 C/T polymorphism was performed in 254 subjects (168

women and 86 men). The main characteristics of the study population, according to

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Joana Barroso

genotype are in table 6. There were 110(43.3%) participants with CC genotype,

106(41.7%) heterozygotes CT, and 38(15.0%) homozygotes TT. Genotype and allele


The relative frequency of the -511T allele was 0.36.

Table 6. Subjects’ characteristics according to the IL1� -511C/T genotype

C/C C/T T/T p

N (%) 110(43.3) 106(41.7) 38(15.0) ---

Gender Male n(%)

Female n(%)

34(30.9)

76(69.1)

36(34.0)

70(66.0)

16(42.1)

22(57.9)

0.453

Age (years)a 55.3±15.78 55.4±16.83 56.0±15.93 0.970

Body weight (kg)a 71.8±15.78 67.9±13.31 70.8±15.59 0.145

BMI (kg/m2)a 28. ±5.54 26.5±5.14 27.6±5.11 0.085

Waist (cm)a 93.5±13.79 89.4±12.93 92.7±14.68 0.081

Hip (cm)a 103.0±9.49 100.7±9.22 101.7±8.99 0.187

WHRa 0.9±0.08 0.9±0.08 0.9±0.09 0.186

Fat Mass (kg)a 23.8±9.92 20.5±9.26 21.6±9.74 0.045

Free Fat Mass (kg)a 47.9±9.64 47.3±8.73 48.5±10.84 0.776

a Results are expressed as mean ± SD. BMI, body mass index; WHR, waist-hip ratio.

When we evaluated markers of obesity, according to IL1� -511C/T genotype, we found

significant differences for fat mass (p=0.045) (table 6).

When comparing homozygotes CC with T carriers, significant associations remained for

fat mass (�=-2.905, p=0.011) and additionally for body weight (�=-3.834, p=0.026), BMI

(�=-1.327, p=0.037), waist circumference (�=-3.624, p=0.018) and waist-hip ratio (�=-

0.018, p=0.036), when adjusted for age and gender (table 7).

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Joana Barroso

Table 7. Subjects’ characteristics according to IL1� -511C/T allele, adjusted for age and gender

T carriera C carrierb

� p* � p*

Body weight (kg) -3.834 0.026 0.400 0.868

BMI (kg/m2) -1.327 0.037 -0.243 0.785

Waist (cm) -3.624 0.018 -0.273 0.898

Hip (cm) -2.037 0.075 0.174 0.913

WHR -0.018 0.036 -0.003 0.831

Fat Mass (kg) -2.905 0.011 0.294 0.855

Free Fat Mass (kg) -0.943 0.205 0.355 0.733

BMI, body mass index; WHR, waist-hip ratio. a Reference class - homozygotes C/C b Reference class - homozygotes T/T p*, p value adjusted for age and gender.

CRP levels revealed no significant differences when comparing homozigotes CC with

heterozigotes CT (�=-0.165, p=0.271) and homozigotes TT (�=-0.394, p=0.058).

It was found no interaction between waist circumference and homozigotes TT, in relation

to CRP concentrations. The interaction of homozigotes CC (�=0.027, p<0.001) and

heterozigotes CT (�= -0.027, p<0.001) with WC showed an effect on CRP concentrations,

even after adjustment for gender, age and smoking habits (table 8).

In relation to WHR, there was an interaction with homozigotes CC, increasing CRP levels

(�= 3.078, p=0.013) (table 8).

Table 8. The effect of IL1� -511C/T polymorphism in the association between waist circumference and waist-to-hip ratio

with CRP levels.

Crude Adjusted*

IL1� -511C/T WC WCxCT WCxTT WC WCxCT WCxTT

� 0.027 -0.027 -0.012 0.026 -0.026 -0.006

p <0.001 <0.001 0.402 <0.001 <0.001 0.630

IL1� -511C/T WHR WHRxCT WHRxTT WHR WHRxCC WHRxTT

� 3.078 0.676 -1.517 4.249 0.040 -1.260

p 0.013 0.701 0.524 0.002 0.981 0.588


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Joana Barroso

Leukocytes levels revealed no significant differences when comparing homozigotes CC

with heterozigotes CT (�=0.017, p=0.934) and homozigotes TT (�=0.018, p=0.951).

It was found no interaction between waist circumference and C carriers. Once adjusted for

gender, age and smoking habits, the interaction between waist circumference and CC

homozigotes (�=0.028, p=0.009) and heterozigotes CT (�= -0.026, p=0.018) affected

leukocyte levels (table 9).



with leukocytes

Crude Adjusted*


� 0.020 -0.018 -0.024 0.028 -0.026 -0.020

p 0.063 0.097 0.246 0.009 0.018 0.338


� 1.631 0.841 -1.846 3.279 0.556 -1.744

p 0.348 0.738 0.598 0.092 0.823 0.612


Uric acid levels revealed no significant differences when comparing homozigotes CC with

heterozigotes CT (�=-1.078, p=0.591) and homozigotes TT (�=-2.589, p=0.359).


to uric acid concentrations. The interaction of homozigotes CC (�=0.586, p<0.001) and

heterozigotes CT (�= -0.543, p<0.001) with WC showed an effect on uric acid levels, even

after adjustment for gender, age and smoking habits (table 10).

In relation to WHR, there was an interaction with homozigotes CC, increasing uric acid

levels (�= 90.87, p<0.001) (table 10).

52

Joana Barroso


with uric acid

Crude Adjusted*


� 0.586 -0.543 -0.271 0.467 -0.437 -0.258

p <0.001 <0.001 0.145 <0.001 <0.001 0.131


� 90.870 -16.550 -38.930 57.033 -17.377 -26.822

p <0.001 0.446 0.199 <0.001 0.413 0.363


Fibrinogen levels revealed no significant differences when comparing homozigotes CC

with heterozigotes CT (�=0.151, p=0.280) and homozigotes TT (�=-0.068, p=0.723).


to fibrinogen concentrations. The interaction of homozigotes CC (�=0.016, p=0.038) and

heterozigotes CT (�= -0.018, p=0.021) with WC showed an effect on fibrinogen

concentrations. After adjustment for gender, age and smoking habits, the interactions

(WCxCC, WCxCT) effect on fibrinogen levels remained statistically significant (table 11).

In relation to WHR, after adjustment for gender, age and smoking habits, there was an

interaction with homozigotes CC, increasing fibrinogen levels (�=2.927, p=0.029) (table

11).


with fibrinogen

Crude Adjusted*


� 0.016 -0.018 -0.020 0.015 -0.017 -0.017

p 0.038 0.021 0.136 0.053 0.028 0.185


� 2.397 0.130 -2.060 2.927 -0.103 -1.822

p 0.051 0.943 0.366 0.029 0.954 0.414


53

Joana Barroso

Genotyping of the TNF-� -308 G/A polymorphism was performed in 308 subjects (205

women and 103 men). The main characteristics of the study population, according to

genotype are in table 12. There were 228(74.0%) participants with GG genotype,

76(24.7%) heterozygotes GA, and 4(1.3%) homozygotes AA. Genotype and allele


The relative frequency of the -308A allele was 0.14.

Table12. Subjects’ characteristics according to the TNF-� -308 G/A genotype

G/G G/A A/A p

N (%) 228(74) 76(24.7) 4(1.3) ---

Gender Male n(%)

Female n(%)

82(36.0)

146(64.0)

21(27.6)

55(72.4)

0(0.0)

4(100.0)

0.148

Age (years)a 55.0±16.11 55.8±14.66 51.0±19.58 0.814

Body weight (kg)a 69.8±14.63 68.4±12.14 64.78±4.83 0.612

BMI (kg/m2)a 27.1±5.37 27.3±4.63 25.3±3.42 0.740

Waist (cm)a 90.8±13.14 91.1±12.25 89.8±6.69 0.967

Hip (cm)a 101.5±9.10 101.4±8.95 99.9±4.31 0.946

WHRa 0.9±0.08 0.9±0.08 0.9±0.05 0.934

Fat Mass (kg)a 21.6±9.78 22.2±8.80 23.0±4.74 0.865

Free Fat Mass (kg)a 47.9±9.40 46.2±7.69 41.5±3.15 0.155

a Results are expressed as mean ± SD. BMI, body mass index; WHR, waist-hip ratio.

We didn’t see any statistical significant difference between genotypes for the obesity

indices (table 12), even when comparing between alleles (table 13).

54

Joana Barroso

Table 13. Subjects’ characteristics according to TNF-� -308 G/A allele, adjusted for age and gender

A carriera G carrierb

� p* � p*

Body weight (kg) -0.681 0.691 0.790 0.905

BMI (kg/m2) -0.050 0.937 1.801 0.464

Waist (cm) 0.519 0.731 -1.903 0.745

Hip (cm) -0.428 0.706 1.838 0.676

WHR 0.009 0.271 -0.037 0.253

Fat Mass (kg) 0.115 0.920 -0.416 0.924

Free Fat Mass (kg) -0.501 0.502 1.256 0.659

BMI, body mass index; WHR, waist-hip ratio. a Reference class - homozygotes G/G b Reference class - homozygotes A/A p*, p value adjusted for age and gender.

CRP levels revealed no significant differences when comparing homozigotes GG with

heterozigotes GA (�=0.162, p=0.256) and homozigotes AA (�=0.737, p=0.175).

It was found no interaction between waist circumference and homozigotes GG and AA, in

relation to CRP concentrations. The interaction of heterozigotes GA with WC showed an

effect on CRP concentrations (�= 0.038, p<0.001), even after adjustment for gender, age

and smoking habits (table 14).

In relation to WHR, there was an interaction with homozigotes GG, increasing CRP levels

(�= 2.141, p=0.014) (table 14).

Table 14. The effect of TNF-� -308 G/A polymorphism in the association between waist circumference and waist-to-hip ratio

with CRP levels.

Crude Adjusted*

TNF-� -308 G/A WC WCxGA WCxAA WC WCxGA WCxAA

� 0.000 0.038 0.091 0.000 0.034 0.102

p 0.801 <0.001 0.320 0.926 <0.001 0.257

TNF-� -308 G/A WHR WHRxGA WHRxAA WHR WHRxGA WHRxAA

� 2.141 1.735 -4.594 3.137 0.873 -4.180

p 0.014 0.336 0.706 0.002 0.624 0.725


55

Joana Barroso

Leukocytes levels revealed no significant differences when comparing homozigotes GG

with heterozigotes GA (�=-0.332, p=0.123) and homozigotes AA (�=-0.594, p=0.485).

It was found no interaction between waist circumference and GG, GA and AA genotypes,

in relation to leukocytes concentrations (table 15).



with leukocytes.

Crude Adjusted*


� 0.002 0.017 0.187 0.003 0.026 0.278

p 0.234 0.271 0.199 0.121 0.092 0.050


� 1.998 1.830 27.935 2.975 1.191 36.542

p 0.113 0.505 0.148 0.049 0.657 0.051

WC, waist circumference; WHR, waist to hip ratio. *Adjusted for age, gender, smoking habits and the main effect of the polymorphism. Uric acid levels revealed no significant differences when comparing homozigotes GG with

heterozigotes GA (�=-1.080, p=0.580) and homozigotes AA (�=-4.766, p=0.536).

The interaction of homozigotes GG and GA with WC showed an effect on uric acid

concentrations (�=0.056, p<0.001 and �=0.410, p=0.003, respectively), even after

adjustment for gender, age and smoking habits (table 16). It was found no interaction

between waist circumference and homozigotes AA, in relation to uric acid concentrations.

In relation to WHR, there was an interaction with homozigotes GG, increasing uric acid

levels (�= 82.08, p<0.001) (table 16).

56

Joana Barroso


with uric acid

Crude Adjusted*


� 0.056 0.410 0.420 0.038 0.336 0.095

p <0.001 0.003 0.743 0.008 0.009 0.934


� 82.085 -11.035 -81.076 46.687 -3.420 -73.913

p <0.001 0.628 0.610 <0.001 0.876 0.625


Fibrinogen levels revealed no significant differences when comparing homozigotes GG

with heterozigotes GA (�=-0.041, p=0.770) and homozigotes AA (�=-0.117, p=0.806).

It was found no interaction between waist circumference and genotypes GG, GA and AA,

in relation to fibrinogen concentrations. After adjustment for gender, age and smoking

habits, the interaction of homozigotes GG (�=-0.002, p=0.034) and heterozigotes GA (�=

0.017, p=0.001) with WC showed an effect on fibrinogen concentrations (table 17).

In relation to WHR, after adjustment for gender, age and smoking habits, there was an

interaction with homozigotes GG, increasing fibrinogen levels (�=1.958, p=0.046) (table

17).

Table17. The effect of TNF-� -308 G/A polymorphism in the association between waist circumference and waist-to-hip ratio

with fibrinogen

Crude Adjusted*


� -0.002 0.020 -0.058 -0.002 0.017 0.018

p 0.053 0.120 0.845 0.034 0.001 0.162


� 1.602 1.880 -3.951 1.958 1.030 -3.575

p 0.054 0.368 0.770 0.046 0.618 0.786


57

Joana Barroso

DISCUSSION

58

Joana Barroso

DISCUSSION

In common multifactorial diseases, the interaction between genes and the environment is

subtle and complex: susceptibility genes modulate the effect of environmental risk factors,

making the initial pathologic event more or less likely 103. Whether this pathologic event

triggers the development of a clinically detectable disease, and how fast the disease

develops, is influenced by genetic modifiers that exaggerate or suppress disease

progression 103. One example in which genes may act as both susceptibility factors and

modifiers for some disease states can be found in the cytokine system 103. It is possible to

postulate that genetic variation affecting the activity of certain cytokine genes may

produce individuals with a more exaggerated or prolonged inflammatory response 103.

Therefore, we analysed three polymorphisms encoding for IL6, IL1� and TNF-� genes,

and their relation to fat, regarding four inflammatory markers levels.

As expected 62 104 105, we saw a significant correlation between the four inflammatory

markers, since they are all involved in the complexity of inflammatory process. Obesity

has been associated with higher levels of CRP 89, and in our study we found a positive

correlation between CRP levels and obesity indices. Other studies presented the same

results 92 95 106, indicating a potential role of this acute-phase protein in the obesity

inflammatory process. Uric acid, leukocytes, and fibrinogen also showed positive

correlation with a few obesity indices, as it was previously seen 94 107 108.

Interleukin 6

For IL6 -174G/C polymorphism, we genotyped 322 individuals, of whom 44.7% were GG

homozygotes, 41.0% were heterozygotes and 14.3% were CC homozygotes. The

59

Joana Barroso

frequency of the -174C allele was 0.35, which is close to other European Caucasian

populations 37 84.

In our formerly study (unpublished data) we noticed that CRP plasma levels were not

significantly different according to genotypes, when comparing homozigotes GG with

heterozigotes GC, but when evaluated the interaction between WC and IL6

polymorphism, there was a significant association between waist circumference and C

carriers, with heterozigotes GC and homozigotes CC presenting higher CRP levels than

homozigotes GG.

In this study we observe similar results in two other inflammatory markers, uric acid and

leukocytes (after adjustment). Given that IL-6 is involved in hematopoiesis 109, we suggest

that these associations might in part be due to adipocytes sitmulation of IL6 production

and different fat IL-6 levels attributed to the IL-6 polymorphism at position –174. We

couldn’t probably saw the same results for fibrinogen because of the small number of

people with CC genotype and measured levels of fibrinogen, but there is a nonsignificant

trend toward elevated levels in C carriers. In a study with 598 adult participants, plasma

fibrinogen levels did not differ among patients with the different genotypes of IL6 -174G/C

polymorphism 110, although some in vitro studies showed that IL6 has a direct effect on

transcription of the fibrinogen �, � and � genes 111 112.

Interleukin 1�

For IL1� -511C/T we genotyped 254 individuals, of whom 43.3% were CC, 41.7% were

heterozygotes CT, and 15.0% were homozygotes TT. The relative frequency of the -511T

allele was 0.36, which is close to other previous studies 19 113 114.

60

Joana Barroso

In our study, there were only differences between genotypes for fat mass, but when we

compared T carriers with CC homozigotes, they presented lower levels of body weight,

BMI, WC, WHR and fat mass. Although we cannot discard other interactions and

haplotypes effect, it seems that T allele carriers are more prone to have lower obesity

indices, than homozigotes CC.

Since that IL1� -511 T allele has been related to higher levels of the cytokine 17-19, and

given that IL1 plays a key role in autoimmune and inflammatory diseases, we expected to

see it related with higher inflammatory levels, given that inflammation itself proceeds like a

cascade, and therefore only minor adjustments at the beginning of this process could

have a major outcome at the end of the process. Even though, we found no differences

between the three genotypes, regarding inflammatory markers levels. IL1 acts early in the

cascade of inflammatory response, inducing the reaction, and it could be that at

intermediate steps of the inflammatory process, other inflammatory mediators interact with

IL1 inducing a protective effect from excessively strong inflammatory reactions by this

genotype.

When we evaluated the interaction between abdominal fat and IL1� -511C/T

polymorphism, within inflammatory markers levels showed a statistically significant

interaction for heterozigotes and a nonsignificant trend toward lower inflammatory levels

for TT homozigotes. As IL1� -511C/T polymorphism alone has no effect on inflammatory

markers levels, and since the T allele is related with lower obesity indices, we could

hypothesized that the interaction of T allele with abdominal fat originates lower indices of

adiposity, and therefore lower inflammation levels, since that increased adipose mass

contributes directly toward an increase in systemic inflammation 115.

61

Joana Barroso

Tumor necrosis factor- �

Genotyping of the TNF-� -308 G/A polymorphism was performed in 308 subjects, 74.0%

with GG genotype, 24.7% heterozygotes GA, and 1.3% homozygotes AA. The relative

frequency of the -308A allele was 0.14. The allelic frequency is in accordance with allelic

frequencies observed in other studies in Caucasian populations 116 117.

Fat tissue is a significant source of endogenous TNF� production and the expression of

this cytokine is elevated in human obesity in adipose tissue 20 118, thus TNF� was

considered as a candidate gene for obesity. Although, as it was previously shown 119,

there were no significant differences between the genotype groups with respect to

estimates of obesity and body fat distribution. In a study with 284 participants, no

significant differences were found between TNF� -308G/A genotypes and BMI and waist-

hip ratio 119. Results from other studies, investigating TNF-� gene effects on obesity, lipid

metabolism and anthropometric parameters, also found no association between

genotypes and these parameters 120 121. Higher production of TNF� linked to -308A variant

may induce adipose tissue development by increasing the total number of stromal-

vascular and/or uncommitted cells within the tissue, given that Kras et al. 122 have

reported that these cells may be recruited to become preadipocytes or may serve

alternatively as infrastructure to support adiposity growth. Even though, it is noteworthy

that the patogenesis of obesity is complex, probably involving several genes and

environmental factors, and therefore, we couldn’t saw any differences between

genotypes.

When we evaluated inflammatory markers levels according to genotype, there were no

statistically significant differences. Further analysis of interaction between waist

circumference and TNF� -308G/A polymorphism, within inflammatory markers levels,

62

Joana Barroso

showed a statistically significant interaction for heterozigotes and a nonsignificant trend

toward higher inflammatory levels for AA homozigotes. This nonsignificant trend was

probably caused by the lower number of people with AA genotype, since the elevation in

inflammatory markers levels is quite notorious when compared with GG homozigotes.

Provided that T allele is related to higher TNF� levels 29, and that has been demonstrated

that adipocytes are responsive to TNF�, with a downstream activation of inflammatory

signalling cascades 123, we postulate that this could be one possible interaction between

abdominal fat and TNF� -308G/A polymorphism that gives rise to higher inflammatory

levels.

This study has limitations. We couldn’t perform genotyping for the three polymorphism, in

all participants, nonetheless we presented allele frequencies similar to those previously

reported. We were also not able to genotype other potentially functional variations in the

genes locus so that such interference could be ruled out. The finding of a relationship

between the interaction of some polymorphisms and fat distribution, regarding

inflammatory markers, is a statistical finding, which does not clarify causality, but we can

hypothesized that polymorphisms show phenotipically expression only in combination with

other risk factors. To the best of our knowledge, no other study tried to evaluate the

interaction between polymorphisms and abdominal adiposity within inflammatory markers

levels and although we observed an interaction, we cannot elucidate the mechanisms

responsible for the interactions described. Thus, which factors linked to WC and cytokine

genes expressions dependent on the respective analyzed polymorphisms differentially

regulate inflammatory levels remains to be evaluated.

63

Joana Barroso

64

Joana Barroso

CONCLUSION

65

Joana Barroso

CONCLUSION

In the study we tried to evaluate the interaction between obesity, especially abdominal

adiposity and few polymorphisms in genes enconding pro-inflammatory cytokines in

relation to four inflammatory markers levels. For each one of the analysed polymorphisms,

there is an interaction with waist circumference in relation to at least one inflammatory

marker level. We found that this interaction has a similar effect on inflammatory markers,

even though not always statistically significant, what could indicate that the genetic effect

is broadcasted for all the inflammatory process. As we cannot assess the mechanisms

responsible for the interactions, further studies are necessary to better evaluate these

interactions and the possible causes

66

Joana Barroso

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67

Joana Barroso

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